Automatic Characterization of Prostate Suspect Lesions on T2-Weighted Image Acquisitions Using Texture Features and Machine-Learning Methods: A Pilot Study

Automatic Characterization of Prostate Suspect Lesions on T2-Weighted Image Acquisitions Using Texture Features and Machine-Learning Methods: A Pilot Study

<b>Background</b>: Prostate cancer (PCa) is the most frequent neoplasia in the male population. According to the International Society of Urological Pathology (ISUP), PCa can be divided into two major groups, based on their prognosis and treatment options. Multiparametric magnetic resona...

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Main Authors: Teodora Telecan, Cosmin Caraiani, Bianca Boca, Roxana Sipos-Lascu, Laura Diosan, Zoltan Balint, Raluca Maria Hendea, Iulia Andras, Nicolae Crisan, Monica Lupsor-Platon
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Diagnostics
Subjects:
radiomics
textural analysis
prostate cancer
mpMRI
artificial intelligence
machine learning
Online Access:https://www.mdpi.com/2075-4418/15/1/106
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